{"id":"https://openalex.org/W4399418425","doi":"https://doi.org/10.1145/3652583.3657623","title":"Near-Miss Accident Prediction on the Edge: A Real-Time System for Safer Driving","display_name":"Near-Miss Accident Prediction on the Edge: A Real-Time System for Safer Driving","publication_year":2024,"publication_date":"2024-05-30","ids":{"openalex":"https://openalex.org/W4399418425","doi":"https://doi.org/10.1145/3652583.3657623"},"language":"en","primary_location":{"id":"doi:10.1145/3652583.3657623","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3657623","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3657623","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3657623","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023083273","display_name":"Minh-Son Dao","orcid":"https://orcid.org/0000-0003-3044-8175"},"institutions":[{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Minh-Son Dao","raw_affiliation_strings":["Big Data Integration Research Center, National Institute of Information and Communications Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Big Data Integration Research Center, National Institute of Information and Communications Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I90023481"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048072689","display_name":"Koji Zettsu","orcid":"https://orcid.org/0000-0003-4062-2376"},"institutions":[{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koji Zettsu","raw_affiliation_strings":["Big Data Integration Research Center, National Institute of Information and Communications Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Big Data Integration Research Center, National Institute of Information and Communications Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I90023481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023083273"],"corresponding_institution_ids":["https://openalex.org/I90023481"],"apc_list":null,"apc_paid":null,"fwci":0.4334,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58803075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1165","last_page":"1169"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.775600790977478},{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.6175765991210938},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.6110524535179138},{"id":"https://openalex.org/keywords/safer","display_name":"SAFER","score":0.604880154132843},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.55322265625},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4677674174308777},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.45970165729522705},{"id":"https://openalex.org/keywords/warning-system","display_name":"Warning system","score":0.43378445506095886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4049844443798065},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34382396936416626},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2443889081478119}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.775600790977478},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.6175765991210938},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6110524535179138},{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.604880154132843},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.55322265625},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4677674174308777},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.45970165729522705},{"id":"https://openalex.org/C29825287","wikidata":"https://www.wikidata.org/wiki/Q1427940","display_name":"Warning system","level":2,"score":0.43378445506095886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4049844443798065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34382396936416626},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2443889081478119},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3652583.3657623","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3657623","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3657623","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3652583.3657623","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3657623","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3657623","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4399418425.pdf"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W2033819227","https://openalex.org/W2125186487","https://openalex.org/W3007708545","https://openalex.org/W3011098590","https://openalex.org/W4296229087","https://openalex.org/W4320014770","https://openalex.org/W4387743899","https://openalex.org/W4391094350"],"related_works":["https://openalex.org/W2953205341","https://openalex.org/W235065745","https://openalex.org/W2029935773","https://openalex.org/W2787754950","https://openalex.org/W1572215850","https://openalex.org/W1985775355","https://openalex.org/W2352115286","https://openalex.org/W2084793300","https://openalex.org/W2476350415","https://openalex.org/W599377045"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"an":[3],"innovative":[4],"approach":[5,90,145],"to":[6,43,71,135,147],"predicting":[7],"near-miss":[8,35,93],"accidents,":[9],"vital":[10],"for":[11,127],"proactive":[12],"accident":[13,36,94,161],"prevention.":[14],"Leveraging":[15],"dashcam":[16],"footage":[17],"and":[18,32,45,64,78,96,141,160],"weather":[19],"sensor":[20],"data,":[21],"our":[22,116,122,144],"model":[23,124],"integrates":[24],"camera":[25],"calibration,":[26],"collision":[27],"point":[28],"prediction,":[29],"heuristic":[30,69],"knowledge,":[31],"analysis":[33,110],"of":[34,57,101,115],"patterns.":[37],"We":[38],"propose":[39],"a":[40,55,98],"comprehensive":[41],"method":[42,117],"detect":[44],"predict":[46],"potential":[47],"collisions":[48],"within":[49],"the":[50,112],"ego-vehicle's":[51],"safe":[52],"zone,":[53],"utilizing":[54],"combination":[56],"machine":[58],"learning":[59],"techniques":[60],"including":[61],"DeepHough,":[62],"YOLOv8,":[63],"LSTM.":[65],"Furthermore,":[66],"we":[67],"introduce":[68],"rules":[70],"handle":[72],"sudden":[73],"changes":[74],"in":[75,157],"object":[76,80],"behavior":[77],"enhance":[79],"detection":[81],"accuracy":[82,100],"under":[83],"challenging":[84],"conditions":[85],"like":[86],"low":[87],"visibility.":[88],"Our":[89],"identifies":[91],"common":[92],"patterns":[95],"achieves":[97],"prediction":[99],"96.01%":[102],"with":[103,139,154],"support":[104],"from":[105],"hard":[106],"brake":[107],"detection.":[108],"Comparative":[109],"demonstrates":[111],"superior":[113],"performance":[114],"against":[118],"existing":[119],"benchmarks.":[120],"Moreover,":[121],"lightweight":[123],"is":[125],"designed":[126],"deployment":[128],"on":[129],"edge":[130],"clients,":[131],"ensuring":[132],"real-time":[133],"assistance":[134,152],"drivers.":[136],"Collaboratively":[137],"developed":[138],"government":[140],"industry":[142],"stakeholders,":[143],"contributes":[146],"creating":[148],"cost-effective":[149],"smart":[150],"driving":[151],"systems":[153],"wide-ranging":[155],"applications":[156],"traffic":[158],"safety":[159],"analysis.":[162]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}